Molecular Mechanisms Underlying Sugarcane Response to Aluminum Stress by RNA-Seq.

Some metals are beneficial to plants and contribute to critical physiological processes. Some metals, however, are not. The presence of aluminum ions (Al3+) can be very toxic, especially in acidic soils. Considerable parts of the world's arable land are acidic in nature; mechanistically elucidating a plant's response to aluminum stress is critical to mitigating this stress and improving the quality of plants. To identify the genes involved in sugarcane response to aluminum stress, we generated 372 million paired-end RNA sequencing reads from the roots of CTC-2 and RB855453, which are two contrasting cultivars. Data normalization resulted in 162,161 contigs (contiguous sequences) and 97,335 genes from a de novo transcriptome assembly (trinity genes). A total of 4858 and 1307 differently expressed genes (DEGs) for treatment versus control were identified for the CTC-2 and RB855453 cultivars, respectively. The DEGs were annotated into 34 functional categories. The majority of the genes were upregulated in the CTC-2 (tolerant cultivar) and downregulated in RB855453 (sensitive cultivar). Here, we present the first root transcriptome of sugarcane under aluminum stress. The results and conclusions of this study are a crucial launch pad for future genetic and genomic studies of sugarcane. The transcriptome analysis shows that sugarcane tolerance to aluminum may be explained by an efficient detoxification mechanism combined with lateral root formation and activation of redox enzymes. We also present a hypothetical model for aluminum tolerance in the CTC-2 cultivar.

Third transmembrane domain of the adrenocorticotropic receptor is critical for ligand selectivity and potency.

The ACTH receptor, known as the melanocortin-2 receptor (MC2R), plays an important role in regulating and maintaining adrenocortical function. MC2R is a subtype of the melanocortin receptor (MCR) family and has unique characteristics among MCRs. Endogenous ACTH is the only endogenous agonist for MC2R, whereas the melanocortin peptides α-, ß-, and γ-melanocyte-stimulating hormone and ACTH are full agonists for all other MCRs. In this study, we examined the molecular basis of MC2R responsible for ligand selectivity using ACTH analogs and MC2R mutagenesis. Our results indicate that substitution of Phe(7) with D-Phe or D-naphthylalanine (D-Nal(2')) in ACTH(1-24) caused a significant decrease in ligand binding affinity and potency. Substitution of Phe(7) with D-Nal(2') in ACTH(1-24) did not switch the ligand from agonist to antagonist at MC2R, which was observed in MC3R and MC4R. Substitution of Phe(7) with D-Phe(7) in ACTH(1-17) resulted in the loss of ligand binding and activity. Molecular analysis of MC2R indicated that only mutation of the third transmembrane domain of MC2R resulted in a decrease in D-Phe ACTH binding affinity and potency. Our results suggest that Phe(7) in ACTH plays an important role in ligand selectivity and that the third transmembrane domain of MC2R is crucial for ACTH selectivity and potency.

Substituted 2-(Dimethylamino)biphenyl-2'-carboxaldehydes as Substrates for Studying n→π* Interactions and as a Promising Framework for Tracing the Bürgi-Dunitz Trajectory.

The Bürgi-Dunitz trajectory traces points along the pathway of bond formation between a nucleophile and electrophile. Previous X-ray crystallographic studies of some molecules containing a nucleophilic nitrogen atom and electrophilic carbonyl group provided some initial evidence for various degrees of bond formation via initial n→π* interactions. Observation of a complete set of points along the trajectory, however, has not yet been attained. In this paper, we present a DFT computational study investigating substituted 2-(dimethylamino)biphenyl-2'-carboxaldehydes as substrates for further examination of n→π* interactions and as a potential framework for more complete tracing of the Bürgi-Dunitz trajectory. These compounds are particulary suitable for study because of the rotational freedom granted by the C-C bond connecting the two aromatic rings allowing the molecule to choose the degree of interaction between the two complementary groups. The extent of interaction is measured by interatomic distance, NBO second-order perturbative analysis energies, volume of transferred electron density as provided by ETS-NOCV analysis, and differences in energies between models that allow for n→π* interactions and those that do not. A series of substituted biphenyls are ultimately identified as future synthetic targets that have maximum potential for providing improved tracing of the Bürgi-Dunitz trajectory.

Preferential binding of an odor within olfactory receptors: a precursor to receptor activation.

Using computational methods, which allow mechanistic insights at a molecular level, we explored the olfactory receptor (OR)-odor interactions for 2 mouse ORs, S79 and S86. Both ORs have been previously experimentally, functionally characterized. The odors used were mostly carboxylic acids, which differed in chain length, substituents on the primary carbon atom-chain and degree of unsaturation. These odors elicited varied activation responses from both ORs. Our studies revealed that both receptors have 2 distinct binding sites. Preferential binding in 1 of the 2 sites is correlated with OR activation. The activating odorants: nonanedioic acid, heptanoic acid, and octanoic acid for OR S79 and nonanoic acid for OR S86 preferentially bind in the region bound by transmembranes (TMs [helical domains]) III, IV, V, and VI. The non excitatory odorants heptanol for S79 and heptanoic acid for S86 showed a greater likelihood of binding in the region bound by TMs I, II, III, and VII. Nanosecond-scale molecular dynamics simulations of the physiologically relevant conditions of docked OR-odorant complexes enabled us to quantitatively assess the roles of individual OR amino acids in odor binding. Amino acid-odorant contact maps and distance determinations over the course of the simulations lend support to our conclusions.

Fecal Microbial Diversity of Coyotes and Wild Hogs in Texas Panhandle, USA.

The ecology of infectious diseases involves wildlife, yet the wildlife interface is often neglected and understudied. Pathogens related to infectious diseases are often maintained within wildlife populations and can spread to livestock and humans. In this study, we explored the fecal microbiome of coyotes and wild hogs in the Texas panhandle using polymerase chain reactions and 16S sequencing methods. The fecal microbiota of coyotes was dominated by members of the phyla Bacteroidetes, Firmicutes, and Proteobacteria. At the genus taxonomic level, Odoribacter, Allobaculum, Coprobacillus, and Alloprevotella were the dominant genera of the core fecal microbiota of coyotes. While for wild hogs, the fecal microbiota was dominated by bacterial members of the phyla Bacteroidetes, Spirochaetes, Firmicutes, and Proteobacteria. Five genera, Treponema, Prevotella, Alloprevotella, Vampirovibrio, and Sphaerochaeta, constitute the most abundant genera of the core microbiota of wild hogs in this study. Functional profile of the microbiota of coyotes and wild hogs identified 13 and 17 human-related diseases that were statistically associated with the fecal microbiota, respectively (p < 0.05). Our study is a unique investigation of the microbiota using free-living wildlife in the Texas Panhandle and contributes to awareness of the role played by gastrointestinal microbiota of wild canids and hogs in infectious disease reservoir and transmission risk. This report will contribute to the lacking information on coyote and wild hog microbial communities by providing insights into their composition and ecology which may likely be different from those of captive species or domesticated animals. This study will contribute to baseline knowledge for future studies on wildlife gut microbiomes.

Change in Urinary Inflammatory Biomarkers and Psychological Health with Gut Microbiome Modulation after Six Months of a Lifestyle Modification Program in Children.

Background: Obesity is a metabolic disorder that negatively impacts the quality of life. Long-term methods such as exercise and low-fat diets can help regulate this health issue, but 93.3 million Americans continue to struggle. Our research investigates if lifestyle changes can affect urinary inflammation markers and psychological aspects through the modification of gut microbiome composition. Methods: Our study included 16 healthy controls with normal BMI as a comparison group and 22 overweight/obese (OW/OB) adolescents. We collected demographic, clinical, psychological, stool, and urine sample data at enrollment and six months after implementing lifestyle modifications. Bacterial genomic data and inflammatory markers in these samples were analyzed. Results: The lifestyle interventions were associated with decreased inflammation and enhanced mental health among overweight teens. We observed differences in bacterial community compositions between healthy participants and those who underwent treatment, including exercise and dietary habit adjustments, although there was no significant change in bacterial species richness. Mental health correlated with gut microbiota compositions without any demographic influences. The research also uncovered connections between inflammatory markers, psychological factors, and gut microbiota phyla through carbohydrate metabolism alterations. Conclusion: Our findings demonstrate that lifestyle modifications are associated with improved mental health and a reduction in inflammation in overweight adolescents by adjusting the gut microbiota composition.

Single-nuclei analysis reveals depot-specific transcriptional heterogeneity and depot-specific cell types in adipose tissue of dairy cows.

Adipose tissue (AT) is an endocrine organ with a central role on whole-body energy metabolism and development of metabolic diseases. Single-cell and single-nuclei RNA sequencing (scRNA-seq and snRNA-seq, respectively) analyses in mice and human AT have revealed vast cell heterogeneity and functionally distinct subtypes that are potential therapeutic targets to metabolic disease. In periparturient dairy cows, AT goes through intensive remodeling and its dysfunction is associated with metabolic disease pathogenesis and decreased productive performance. The contributions of depot-specific cells and subtypes to the development of diseases in dairy cows remain to be studied. Our objective was to elucidate differences in cellular diversity of visceral (VAT) and subcutaneous (SAT) AT in dairy cows at the single-nuclei level. We collected matched SAT and VAT samples from three dairy cows and performed snRNA-seq analysis. We identified distinct cell types including four major mature adipocytes (AD) and three stem and progenitor cells (ASPC) subtypes, along with endothelial cells (EC), mesothelial cells (ME), immune cells, and pericytes and smooth muscle cells. All major cell types were present in both SAT and VAT, although a strong VAT-specificity was observed for ME, which were basically absent in SAT. One ASPC subtype was defined as adipogenic (PPARG+) while the other two had a fibro-adipogenic profile (PDGFRA+). We identified vascular and lymphatic EC subtypes, and different immune cell types and subtypes in both SAT and VAT, i.e., macrophages, monocytes, T cells, and natural killer cells. Not only did VAT show a greater proportion of immune cells, but these visceral immune cells had greater activation of pathways related to immune and inflammatory response, and complement cascade in comparison with SAT. There was a substantial contrast between depots for gene expression of complement cascade, which were greatly expressed by VAT cell subtypes compared to SAT, indicating a pro-inflammatory profile in VAT. Unprecedently, our study demonstrated cell-type and depot-specific heterogeneity in VAT and SAT of dairy cows. A better understanding of depot-specific molecular and cellular features of SAT and VAT will aid in the development of AT-targeted strategies to prevent and treat metabolic disease in dairy cows, especially during the periparturient period.

Phenotypically concordant and discordant monozygotic twins display different DNA copy-number-variation profiles.

The exploration of copy-number variation (CNV), notably of somatic cells, is an understudied aspect of genome biology. Any differences in the genetic makeup between twins derived from the same zygote represent an irrefutable example of somatic mosaicism. We studied 19 pairs of monozygotic twins with either concordant or discordant phenotype by using two platforms for genome-wide CNV analyses and showed that CNVs exist within pairs in both groups. These findings have an impact on our views of genotypic and phenotypic diversity in monozygotic twins and suggest that CNV analysis in phenotypically discordant monozygotic twins may provide a powerful tool for identifying disease-predisposition loci. Our results also imply that caution should be exercised when interpreting disease causality of de novo CNVs found in patients based on analysis of a single tissue in routine disease-related DNA diagnostics.

GenDrux: a biomedical literature search system to identify gene expression-based drug sensitivity in breast cancer.

BACKGROUND: This paper describes the development of a web-based tool, GenDrux, which extracts and presents (over the Internet) information related to the disease-gene-drug nexus. This information is archived from the relevant biomedical literature using automated methods. GenDrux is designed to alleviate the difficulties of manually processing the vast biomedical literature to identify disease-gene-drug relationships. GenDrux will evolve with the literature without additional algorithmic modifications. RESULTS: GenDrux, a pilot system, is developed in the domain of breast cancer and can be accessed at http://www.microarray.uab.edu/drug_gene.pl. GenDrux can be queried based on drug, gene and/or disease name. From over 8,000 relevant abstracts from the biomedical literature related to breast cancer, we have archived a corpus of more than 4,000 articles that depict gene expression-drug activity relationships for breast cancer and related cancers. The archiving process has been automated. CONCLUSIONS: The successful development, implementation, and evaluation of this and similar systems when created may provide clinicians with a tool for literature management, clinical decision making, thus setting the platform for personalized therapy in the future.

Hedgehog/GLI1 Transcriptionally Regulates FANCD2 in Ovarian Tumor Cells: Its Inhibition Induces HR-Deficiency and Synergistic Lethality with PARP Inhibition.

Ovarian cancer (OC) is one of the most lethal type of cancer in women due to a lack of effective targeted therapies and high rates of treatment resistance and disease recurrence. Recently Poly (ADP-ribose) polymerase inhibitors (PARPi) have shown promise as chemotherapeutic agents; however, their efficacy is limited to a small fraction of patients with BRCA mutations. Here we show a novel function for the Hedgehog (Hh) transcription factor Glioma associated protein 1 (GLI1) in regulation of key Fanconi anemia (FA) gene, FANCD2 in OC cells. GLI1 inhibition in HR-proficient OC cells induces HR deficiency (BRCAness), replication stress and synergistic lethality when combined with PARP inhibition. Treatment of OC cells with combination of GLI1 and PARP inhibitors shows enhanced DNA damage, synergy in cytotoxicity, and strong in vivo anticancer responses.

Novel binding motif of ACTH analogues at the melanocortin receptors.

The melanocortin receptor (MCR) subtype family is a member of the GPCR superfamily, and each of them has a different pharmacological profile with regard to the relative potency of the endogenous and synthetic melanocortin peptides. Alpha-MSH and ACTH are endogenous nonselective agonists for MC1R, MC3R, MC4R, and MC5R. In this study, we examined the role of Phe(7) in ACTH on human (h) MC1R, MC3R, and MC4R binding and signaling. Our results indicate that substitution of Phe(7) with d-Nal(2')(7) in ACTH1-24 yields a pharmacological profile different from that for substitution of Phe(7) with d-Nal(2')(7) in MSH in hMC1R, hMC3R, and hMC4R. N-d-Nal(2')(7)-ACTH1-24 is an agonist at hMC3R and hMC4R which did not change the peptide from an agonist to an antagonist at hMC3R and hMC4R. Further experiments indicate that N-d-Nal(2')(7)-ACTH1-17 is the minimal peptide required for hMC3R and hMC4R activation. Single-amino acid substitution studies of d-Nal(2')(7)-ACTH1-17 indicate that amino acid residues 15-17 in N-d-Nal(2')(7)-ACTH1-17 are crucial for hMC3R and hMC4R activation. Substitutions of these amino acid residues reduced or abolished agonist activity at hMC3R and hMC4R. Conformational studies revealed a new beta-turn (Arg(8)-Trp(9)-Gly(10)-Lys(11)) in N-d-Nal(2')(7)-ACTH1-17, compared to the beta-turn-like structure at NDP-alpha-MSH (His(6)-d-Phe(7)-Arg(8)-Trp(9)). Our results suggest that NDP-alpha-MSH and N-d-Nal(2')(7)-ACTH1-17 do not share the same binding site; the highly basic C-terminal fragment (Lys(15)-Lys(16)-Arg(17)) of N-d-Nal(2')(7)-ACTH1-17 induced a new beta-turn, and this shift contributed the selective agonist activity at hMC3R and hMC4R.

Somatic mosaicism for copy number variation in differentiated human tissues.

Two major types of genetic variation are known: single nucleotide polymorphisms (SNPs), and a more recently discovered structural variation, involving changes in copy number (CNVs) of kilobase- to megabase-sized chromosomal segments. It is unknown whether CNVs arise in somatic cells, but it is, however, generally assumed that normal cells are genetically identical. We tested 34 tissue samples from three subjects and, having analyzed for each tissue < or =10(-6) of all cells expected in an adult human, we observed at least six CNVs, affecting a single organ or one or more tissues of the same subject. The CNVs ranged from 82 to 176 kb, often encompassing known genes, potentially affecting gene function. Our results indicate that humans are commonly affected by somatic mosaicism for stochastic CNVs, which occur in a substantial fraction of cells. The majority of described CNVs were previously shown to be polymorphic between unrelated subjects, suggesting that some CNVs previously reported as germline might represent somatic events, since in most studies of this kind, only one tissue is typically examined and analysis of parents for the studied subjects is not routinely performed. A considerable number of human phenotypes are a consequence of a somatic process. Thus, our conclusions will be important for the delineation of genetic factors behind these phenotypes. Consequently, biobanks should consider sampling multiple tissues to better address mosaicism in the studies of somatic disorders.

Integrated olfactory receptor and microarray gene expression databases.

BACKGROUND: Gene expression patterns of olfactory receptors (ORs) are an important component of the signal encoding mechanism in the olfactory system since they determine the interactions between odorant ligands and sensory neurons. We have developed the Olfactory Receptor Microarray Database (ORMD) to house OR gene expression data. ORMD is integrated with the Olfactory Receptor Database (ORDB), which is a key repository of OR gene information. Both databases aim to aid experimental research related to olfaction. DESCRIPTION: ORMD is a Web-accessible database that provides a secure data repository for OR microarray experiments. It contains both publicly available and private data; accessing the latter requires authenticated login. The ORMD is designed to allow users to not only deposit gene expression data but also manage their projects/experiments. For example, contributors can choose whether to make their datasets public. For each experiment, users can download the raw data files and view and export the gene expression data. For each OR gene being probed in a microarray experiment, a hyperlink to that gene in ORDB provides access to genomic and proteomic information related to the corresponding olfactory receptor. Individual ORs archived in ORDB are also linked to ORMD, allowing users access to the related microarray gene expression data. CONCLUSION: ORMD serves as a data repository and project management system. It facilitates the study of microarray experiments of gene expression in the olfactory system. In conjunction with ORDB, ORMD integrates gene expression data with the genomic and functional data of ORs, and is thus a useful resource for both olfactory researchers and the public.

AlzPharm: integration of neurodegeneration data using RDF.

BACKGROUND: Neuroscientists often need to access a wide range of data sets distributed over the Internet. These data sets, however, are typically neither integrated nor interoperable, resulting in a barrier to answering complex neuroscience research questions. Domain ontologies can enable the querying heterogeneous data sets, but they are not sufficient for neuroscience since the data of interest commonly span multiple research domains. To this end, e-Neuroscience seeks to provide an integrated platform for neuroscientists to discover new knowledge through seamless integration of the very diverse types of neuroscience data. Here we present a Semantic Web approach to building this e-Neuroscience framework by using the Resource Description Framework (RDF) and its vocabulary description language, RDF Schema (RDFS), as a standard data model to facilitate both representation and integration of the data. RESULTS: We have constructed a pilot ontology for BrainPharm (a subset of SenseLab) using RDFS and then converted a subset of the BrainPharm data into RDF according to the ontological structure. We have also integrated the converted BrainPharm data with existing RDF hypothesis and publication data from a pilot version of SWAN (Semantic Web Applications in Neuromedicine). Our implementation uses the RDF Data Model in Oracle Database 10g release 2 for data integration, query, and inference, while our Web interface allows users to query the data and retrieve the results in a convenient fashion. CONCLUSION: Accessing and integrating biomedical data which cuts across multiple disciplines will be increasingly indispensable and beneficial to neuroscience researchers. The Semantic Web approach we undertook has demonstrated a promising way to semantically integrate data sets created independently. It also shows how advanced queries and inferences can be performed over the integrated data, which are hard to achieve using traditional data integration approaches. Our pilot results suggest that our Semantic Web approach is suitable for realizing e-Neuroscience and generic enough to be applied in other biomedical fields.

NeuroExtract: facilitating neuroscience-oriented retrieval from broadly-focused bioscience databases using text-based query mediation.

This paper describes NeuroExtract, a pilot system which facilitates the integrated retrieval of Internet-based information relevant to the neurosciences. The approach involved extracting descriptive metadata from the sources using domain-specific queries; retrieving, processing, and organizing the data into structured text files; searching the data files using text-based queries; and, providing the results in a Web page along with descriptions to entries and URL links to the original sources. NeuroExtract has been implemented for three bioscience resources, SWISSPROT, GEO, and PDB, which provide neuroscience-related information as sub-topics. We discuss several issues that arose in the course of NeuroExtract's implementation. This project is a first step in exploring how this general approach might be used, in conjunction with other query mediation approaches, to facilitate the integration of many Internet-accessible resources relevant to the neurosciences.

Managing knowledge in neuroscience.

Processing text from scientific literature has become a necessity due to the burgeoning amounts of information that are fast becoming available, stemming from advances in electronic information technology. We created a program, NeuroText ( http://senselab.med.yale.edu/textmine/neurotext.pl ), designed specifically to extract information relevant to neuroscience-specific databases, NeuronDB and CellPropDB ( http://senselab.med.yale.edu/senselab/ ), housed at the Yale University School of Medicine. NeuroText extracts relevant information from the Neuroscience literature in a two-step process: each step parses text at different levels of granularity. NeuroText uses an expert-mediated knowledge base and combines the techniques of indexing, contextual parsing, semantic and lexical parsing, and supervised and non-supervised learning to extract information. The constrains, metadata elements, and rules for information extraction are stored in the knowledge base. NeuroText was created as a pilot project to process 3 years of publications in Journal of Neuroscience and was subsequently tested for 40,000 PubMed abstracts. We also present here a template to create domain non-specific knowledge base that when linked to a text-processing tool like NeuroText can be used to extract knowledge in other fields of research.

Olfactory Receptor Database: a metadata-driven automated population from sources of gene and protein sequences.

The Olfactory Receptor Database (ORDB; http://senselab.med.yale.edu/senselab/ordb) is a central repository of olfactory receptor (OR) and olfactory receptor-like gene and protein sequences. To deal with the very large OR gene family, we have constructed an algorithm that automatically downloads sequences from web sources such as GenBank and SWISS-PROT into the database. The algorithm uses hypertext markup language (HTML) parsing techniques that extract information relevant to ORDB. The information is then correlated with the metadata in the ORDB knowledge base to encode the unstructured text extracted into the structured format compliant with the database architecture, entity attribute value with classes and relationship (EAV/CR), which supports the SenseLab project as a whole. Three population methods: batch, automatic and semi-automatic population are discussed. The data is imported into the database using extensible markup language (XML).

ORDB, HORDE, ODORactor and other on-line knowledge resources of olfactory receptor-odorant interactions.

We present here an exploration of the evolution of three well-established, web-based resources dedicated to the dissemination of information related to olfactory receptors (ORs) and their functional ligands, odorants. These resources are: the Olfactory Receptor Database (ORDB), the Human Olfactory Data Explorer (HORDE) and ODORactor. ORDB is a repository of genomic and proteomic information related to ORs and other chemosensory receptors, such as taste and pheromone receptors. Three companion databases closely integrated with ORDB are OdorDB, ORModelDB and OdorMapDB; these resources are part of the SenseLab suite of databases (http://senselab.med.yale.edu). HORDE (http://genome.weizmann.ac.il/horde/) is a semi-automatically populated database of the OR repertoires of human and several mammals. ODORactor (http://mdl.shsmu.edu.cn/ODORactor/) provides information related to OR-odorant interactions from the perspective of the odorant. All three resources are connected to each other via web-links.Database URL: http://senselab.med.yale.edu; http://genome.weizmann.ac.il/horde/; http://mdl.shsmu.edu.cn/ODORactor/.

Text mining neuroscience journal articles to populate neuroscience databases.

We have developed a program NeuroText to populate the neuroscience databases in SenseLab (http://senselab.med.yale.edu/senselab) by mining the natural language text of neuroscience articles. NeuroText uses a two-step approach to identify relevant articles. The first step (pre-processing), aimed at 100% sensitivity, identifies abstracts containing database keywords. In the second step, potentially relevant abstracts identified in the first step are processed for specificity dictated by database architecture, and neuroscience, lexical and semantic contexts. NeuroText results were presented to the experts for validation using a dynamically generated interface that also allows expert-validated articles to be automatically deposited into the databases. Of the test set of 912 articles, 735 were rejected at the pre-processing step. For the remaining articles, the accuracy of predicting database-relevant articles was 85%. Twenty-two articles were erroneously identified. NeuroText deferred decisions on 29 articles to the expert. A comparison of NeuroText results versus the experts' analyses revealed that the program failed to correctly identify articles' relevance due to concepts that did not yet exist in the knowledgebase or due to vaguely presented information in the abstracts. NeuroText uses two "evolution" techniques (supervised and unsupervised) that play an important role in the continual improvement of the retrieval results. Software that uses the NeuroText approach can facilitate the creation of curated, special-interest, bibliography databases.